Download or read book Stochastic Mortality Modeling and Securitization of Mortality Risk written by Daniel Bauer and published by . This book was released on 2008 with total page 242 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Mortality Risk Modeling written by Samuel H. Cox and published by . This book was released on 2011 with total page 35 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper proposes a stochastic mortality model featuring both permanent longevity jump and temporary mortality jump processes. A trend reduction component describes unexpected mortality improvement over an extended period of time. The model also captures the uneven effect of mortality events on different ages and the correlations among them. The model will be useful in analyzing future mortality dependent cash flows of life insurance portfolios, annuity portfolios, and portfolios of mortality derivatives. We show how to apply the model to analyze and price a longevity security.

Download or read book Stochastic Mortality Modelling written by Xiaoming Liu and published by . This book was released on 2008 with total page 380 pages. Available in PDF, EPUB and Kindle. Book excerpt: For life insurance and annuity products whose payoffs depend on the future mortality rates, there is a risk that realized mortality rates will be different from the anticipated rates accounted for in their pricing and reserving calculations. This is termed as mortality risk. Since mortality risk is difficult to diversify and has significant financial impacts on insurance policies and pension plans, it is now a well-accepted fact that stochastic approaches shall be adopted to model the mortality risk and to evaluate the mortality-linked securities.To be more specific, we consider a finite-state Markov process with one absorbing state. This Markov process is related to an underlying aging mechanism and the survival time is viewed as the time until absorption. The resulting distribution for the survival time is a so-called phase-type distribution. This approach is different from the traditional curve fitting mortality models in the sense that the survival probabilities are now linked with an underlying Markov aging process. Markov mathematical and phase-type distribution theories therefore provide us a flexible and tractable framework to model the mortality dynamics. And the time-changed Markov process allows us to incorporate the uncertainties embedded in the future mortality evolution.The proposed model has been applied to price the EIB/BNP Longevity Bonds and other mortality derivatives under the independent assumption of interest rate and mortality rate. A calibrating method for the model is suggested so that it can utilize both the market price information involving the relevant mortality risk and the latest mortality projection. The proposed model has also been fitted to various type of population mortality data for empirical study. The fitting results show that our model can interpret the stylized mortality patterns very well.The objective of this thesis is to propose the use of a time-changed Markov process to describe stochastic mortality dynamics for pricing and risk management purposes. Analytical and empirical properties of this dynamics have been investigated using a matrix-analytic methodology. Applications of the proposed model in the evaluation of fair values for mortality linked securities have also been explored.

Download or read book Stochastic Mortality Modelling written by Xiaoming Jr Liu and published by . This book was released on with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Stochastic Mortality Models and Securitization in Life Insurance written by Sandra Caterina Gaißer and published by . This book was released on 2006 with total page 125 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Stochastic Systematic Mortality Risk Modeling Under Collateral Data and Actuarial Applications written by Joab Onyango Odhiambo and published by Eliva Press. This book was released on 2023-03-26 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many actuaries worldwide use Systematic Mortality Risk (SMR) to value actuarial products such as annuities and assurances sold to policyholders. Data availability plays an essential role in ascertaining the SMR models' accuracy, and it varies from one country to another. Incorrect stochastic modeling of SMR models due to paucity of data has been a problem for many Sub-Saharan African countries such as Kenya, thus prompting modifications of the classical SMR models used in those countries with limited data availability. This study aimed at modelling SMR stochastically under the collateral data environment such as Sub-Saharan African countries like Kenya and then apply it in the current actuarial valuations. This book has formulated novel stochastic mortality risk models under the collateral data setup. Kenya population data is preferably integrated into the commonly applied stochastic mortality risk models under a 3-factor unitary framework of age-time-cohort. After testing SMR models on the Kenyan data to assess their behaviours, we incorporate the Bühlmann Credibility Approach with random coefficients in modeling. The randomness of the classical SMR models was modeled as NIG distribution instead of Normal distribution due to data paucity in Kenya (use of collateral data environment). The Deep Neural Network (DNN) technique solved data paucity during the SMR model fitting and forecasting. The forecasting performances of the SMR models were done under DNN and, compared with those from conventional models, show powerful empirical illustrations in their precision levels. Numerical results showed that SMR models become more accurate under collateral data after incorporating the BCA with NIG assumptions. The Actuarial valuation of annuities and assurances using the new SMR offered much more accurate valuations when compared to those under classical models. The study's findings should help regulators such as IRA and RBA make policy documents that protect all stakeholders in Kenya's insurance, social protection firms, and pension sectors.

Download or read book The Stochastic Mortality Modeling and the Pricing of Mortality longevity Linked Derivatives written by Shuo-Li Chuang and published by . This book was released on 2013 with total page 316 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Lee-Carter mortality model provides the very first model for modeling the mortality rate with stochastic time and age mortality dynamics. The model is constructed modeling the mortality rate to incorporate both an age effect and a period effect. The Lee-Carter model provides the fundamental set up currently used in most modern mortality modeling. Various extensions of the Lee-Carter model include either adding an extra term for a cohort effect or imposing a stochastic process for mortality dynamics. Although both of these extensions can provide good estimation results for the mortality rate, applying them for the pricing of the mortality/ longevity linked derivatives is not easy. While the current stochastic mortality models are too complicated to be explained and to be implemented, transforming the cohort effect into a stochastic process for the pricing purpose is very difficult. Furthermore, the cohort effect itself sometimes may not be significant. We propose using a new modified Lee-Carter model with a Normal Inverse Gaussian (NIG) Lévy process along with the Esscher transform for the pricing of mortality/ longevity linked derivatives. The modified Lee-Carter model, which applies the Lee-Carter model on the growth rate of mortality rates rather than the level of iv mortality rates themselves, performs better than the current mortality rate models shown in Mitchell et al (2013). We show that the modified Lee-Carter model also retains a similar stochastic structure to the Lee-Carter model, so it is easy to demonstrate the implication of the model. We proposed the additional NIG Lévy process with Esscher transform assumption that can improve the fit and prediction results by adapting the mortality improvement rate. The resulting mortality rate matches the observed pattern that the mortality rate has been improving due to the advancing development of technology and improvements in the medical care system. The resulting mortality rate is also developed under a martingale measure so it is ready for the direct application of pricing the mortality/longevity linked derivatives, such as q-forward, longevity bond, and mortality catastrophe bond. We also apply our proposed model along with an information theoretic optimization method to construct the pricing procedures for a life settlement. While our proposed model can improve the mortality rate estimation, the application of information theory allows us to incorporate the private health information of a specific policy holder and hence customize the distribution of the death year distribution for the policy holder so as to price the life settlement. The resulting risk premium is close to the practical understanding in the life settlement market.

Download or read book Stochastic Portfolio Specific Mortality and the Quantification of Mortality Basis Risk written by Richard Plat and published by . This book was released on 2009 with total page 21 pages. Available in PDF, EPUB and Kindle. Book excerpt: The last decennium a vast literature on stochastic mortality models has been developed. However, these models are often not directly applicable to insurance portfolios because: a) For insurers and pension funds it is more relevant to model mortality rates measured in insured amounts instead of measured in number of policies.b) Often there is not enough insurance portfolio specific mortality data available to fit such stochastic mortality models reliably. Therefore, in this paper a stochastic model is proposed for portfolio specific mortality experience. Combining this stochastic process with a stochastic country population mortality process leads to stochastic portfolio specific mortality rates, measured in insured amounts. The proposed stochastic process is applied to two insurance portfolios, and the impact on the Value at Risk for longevity risk is quantified. Furthermore, the model can be used to quantify the basis risk that remains when hedging portfolio specific mortality risk with instruments of which the payoff depends on population mortality rates.

Download or read book Longevity Risk Modeling Securities Pricing and Other Related Issues written by Yinglu Deng and published by . This book was released on 2011 with total page 216 pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation studies the adverse financial implications of "longevity risk" and "mortality risk", which have attracted the growing attention of insurance companies, annuity providers, pension funds, public policy decision-makers, and investment banks. Securitization of longevity/mortality risk provides insurers and pension funds an effective, low-cost approach to transferring the longevity/mortality risk from their balance sheets to capital markets. The modeling and forecasting of the mortality rate is the key point in pricing mortality-linked securities that facilitates the emergence of liquid markets. First, this dissertation introduces the discrete models proposed in previous literature. The models include: the Lee-Carter Model, the Renshaw Haberman Model, The Currie Model, the Cairns-Blake-Dowd (CBD) Model, the Cox-Lin-Wang (CLW) Model and the Chen-Cox Model. The different models have captured different features of the historical mortality time series and each one has their own advantages. Second, this dissertation introduces a stochastic diffusion model with a double exponential jump diffusion (DEJD) process for mortality time-series and is the first to capture both asymmetric jump features and cohort effect as the underlying reasons for the mortality trends. The DEJD model has the advantage of easy calibration and mathematical tractability. The form of the DEJD model is neat, concise and practical. The DEJD model fits the actual data better than previous stochastic models with or without jumps. To apply the model, the implied risk premium is calculated based on the Swiss Re mortality bond price. The DEJD model is the first to provide a closed-form solution to price the q-forward, which is the standard financial derivative product contingent on the LifeMetrics index for hedging longevity or mortality risk. Finally, the DEJD model is applied in modeling and pricing of life settlement products. A life settlement is a financial transaction in which the owner of a life insurance policy sells an unneeded policy to a third party for more than its cash value and less than its face value. The value of the life settlement product is the expected discounted value of the benefit discounted from the time of death. Since the discount function is convex, it follows by Jensen's Inequality that the expected value of the function of the discounted benefit till random time of death is always greater than the benefit discounted by the expected time of death. So, the pricing method based on only the life expectancy has the negative bias for pricing the life settlement products. I apply the DEJD mortality model using the Whole Life Time Distribution Dynamic Pricing (WLTDDP) method. The WLTDDP method generates a complete life table with the whole distribution of life times instead of using only the expected life time (life expectancy). When a life settlement underwriter's gives an expected life time for the insured, information theory can be used to adjust the DEJD mortality table to obtain a distribution that is consistent with the underwriter projected life expectancy that is as close as possible to the DEJD mortality model. The WLTDDP method, incorporating the underwriter information, provides a more accurate projection and evaluation for the life settlement products. Another advantage of WLTDDP is that it incorporates the effect of dynamic longevity risk changes by using an original life table generated from the DEJD mortality model table.

Download or read book Stochastic Mortality written by Annamaria Olivieri and published by . This book was released on 2009 with total page 22 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this paper, we take the point of view of an insurer dealing with life annuities, which aims at building up a (partial) internal model in order to quantify the impact of mortality risks, namely process and longevity risk, in view of taking appropriate risk management actions. We assume that a life table, providing a best-estimate assessment of annuitants' future mortality is available; conversely, no access to data sets and the methodology underlying the construction of the life table is at the insurer's disposal. In spite of this, a stochastic approach is required.We focus on the annual number of deaths in a given cohort, which we model allowing for a random mortality rate. To this purpose, we extend the widely used Poisson model, first assuming a Gamma-distributed random parameter, and second introducing time-dependence in the parameter itself. Further, we define a Bayesian-inferential procedure for updating the parameters to experience in some situations. The setting we define does not demand advanced analytical tools, while allowing for process and longevity risk in a rigorous way.The model is then implemented for capital allocation purposes. We investigate the amount of the required capital for a given life annuity portfolio, based on solvency targets which could be adopted within internal models. The outcomes of such an investigation are compared with the capital required according to some standard rules, in particular those proposed within the Solvency 2 project.

Download or read book Stochastic Mortality Models with Applications in Financial Risk Management written by Siu Hang Li and published by . This book was released on 2007 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Mortality Risk Management written by and published by . This book was released on 2006 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This is a multi-essay dissertation in the area of mortality risk management. The first essay investigates natural hedging between life insurance and annuities and then proposes a mortality swap between a life insurer and an annuity insurer. Compared with reinsurance, capital markets have a greater capacity to absorb insurance shocks, and they may offer more flexibility to meet insurers' needs. Therefore, my second essay studies securitization of mortality risks in life annuities. Specifically I design a mortality bond to transfer longevity risks inherent in annuities or pension plans to financial markets. By explicitly taking into account the jumps in mortality stochastic processes, my third essay fills a gap in the mortality securitization modeling literature by pricing mortality securities in an incomplete market framework. Using the Survey of Consumer Finances, my fourth essay creates a new financial vulnerability index to examine a household's life cycle demand for different types of life insurance.

Download or read book Modelling and Management of Mortality Risk written by Andrew J. G. Cairns and published by . This book was released on 2009 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the first part of the paper, we consider the wide range of extrapolative stochastic mortality models that have been proposed over the last 15-20 years. A number of models that we consider are framed in discrete time and place emphasis on the statistical aspects of modelling and forecasting. We discuss how these models can be evaluated, compared and contrasted. We also discuss a discrete-time market model that facilitates valuation of mortality-linked contracts with embedded options. We then review several approaches to modelling mortality in continuous time. These models tend to be simpler in nature, but make it possible to examine the potential for dynamic hedging of mortality risk. Finally, we review a range of financial instruments (traded and over-the-counter) that could be used to hedge mortality risk. Some of these, such as mortality swaps, already exist, while others anticipate future developments in the market.

Download or read book Affine Stochastic Mortality written by David Schrager and published by . This book was released on 2004 with total page 24 pages. Available in PDF, EPUB and Kindle. Book excerpt: We propose a new model for stochastic mortality. The model is based on the literature on affine term structure models. It satisfies three important requirements for application in practice: analytical tractibility, clear interpretation of the factors and compatibility with financial option pricing models. We test the model fit using data on Dutch mortality rates. Furthermore we discuss the specification of a market price of mortality risk and apply the model to the pricing of a Guaranteed Annuity Option and the calculation of required Economic Capital for mortality risk.

Download or read book Consumption investment Problems with Stochastic Mortality Risk written by Lorenz S. Schendel and published by . This book was released on 2014 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: I numerically solve realistically calibrated life cycle consumption-investment problems in continuous time featuring stochastic mortality risk driven by jumps, unspanned labor income as well as short-sale and liquidity constraints and a simple insurance. I compare models with deterministic and stochastic hazard rate of death to a model without mortality risk. Mortality risk has only minor effects on the optimal controls early in the life cycle but it becomes crucial in later years. A diffusive component in the hazard rate of death has no significant impact, whereas a jump component is desired by the agent and influences optimal controls and wealth evolution. The insurance is used to ensure optimal bequest such that there is no accidental bequest. In the absence of the insurance, the biggest part of bequest is accidental.

Download or read book Improving Longevity and Mortality Risk Models with Common Stochastic Long Run Trends written by Michael Sherris and published by . This book was released on 2011 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Modeling mortality and longevity risk presents challenges because of the impact of improvements at different ages and the existence of common trends. Modeling cause of death mortality rates is even more challenging since trends and age effects are more diverse. Despite this, successfully modeling these mortality rates is critical to assessing risk for insurers issuing longevity risk products including life annuities. Longevity trends are often forecasted using a Lee-Carter model. A common stochastic trend determines age-based improvements. Other approaches fit an age-based parametric model with a time series or vector autoregression for the parameters. Vector Error Correction Models (VECM), developed recently in econometrics, include common stochastic long-run trends. This paper uses a stochastic parameter VECM form of the Heligman-Pollard model for mortality rates, estimated using data for circulatory disease deaths in the United States over a period of 50 years. The model is then compared with a version of the Lee-Carter model and a stochastic parameter ARIMA Heligman-Pollard model. The VECM approach proves to be an improvement over the Lee-Carter and ARIMA models as it includes common stochastic long-run trends.

Download or read book Pandemics Insurance and Social Protection written by María del Carmen Boado-Penas and published by Springer Nature. This book was released on 2022 with total page 314 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book collects expert contributions on actuarial modelling and related topics, from machine learning to legal aspects, and reflects on possible insurance designs during an epidemic/pandemic. Starting by considering the impulse given by COVID-19 to the insurance industry and to actuarial research, the text covers compartment models, mortality changes during a pandemic, risk-sharing in the presence of low probability events, group testing, compositional data analysis for detecting data inconsistencies, behaviouristic aspects in fighting a pandemic, and insurers' legal problems, amongst others. Concluding with an essay by a practicing actuary on the applicability of the methods proposed, this interdisciplinary book is aimed at actuaries as well as readers with a background in mathematics, economics, statistics, finance, epidemiology, or sociology.